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Notes -
Award-Winning AIs
To be fair, "best isekai light novel" is somewhere between 'overly narrow superlative' and 'damning with faint praise', and it's not clear exactly where how predominately AI-generated the writing is or what procedure the human involved used. My own experience has suggested that extant LLMs don't scale well to full short stories without constant direction every 600-1k words, but that is still a lot faster than writing outright, and there are plausible meta-prompt approaches that people have used with some success for coherence, if not necessarily for quality.
Well, that's just the slop-optimizing machine winning in a slop competition.
It's a slightly higher standard than isekai (or country music), and Spotify is a much broader survey mechanism than Random Anime House, and a little easier to check for native English speakers. My tastes in music are...
badunusual, but the aigen seems... fine? Not amazing, by any means, and some artifacts, but neither does it seem certain that the billboard number is just bot activity.Well, that's not the professional use!
It's... hard to tell how much of this is an embarrassing truth specific to Studio Larian, or if it's just the first time someone said it out loud (and Larian did later claim to roll back some of it). Clair Obscur had a prestigious award revoked after the game turned out to have a handful of temporary assets that were AIgen left in a before-release-patch build. ARC Raiders uses a text-to-speech voice cloning tool for adaptive voice lines. But a studio known for its rich atmospheric character and setting art doing a thing is still a data point.
(and pointedly anti-AI artists have gotten to struggle with it and said they'd draw the line here or there. We'll see if that lasts.)
And that seems like just the start?
It's easy to train a LORA to insert your character or characters into parts of a scene, to draw a layout and consider how light would work, or to munge composition until it points characters the right way. StableDiffusion's initial release came with a bunch of oft-ignored helpers for classically extremely tedious problems like making a texture support seamless tiling. Diffusion-based upscaling would be hard to detect even with access to raw injest files. And, of course, DLSS is increasingly standard for AAA and even A-sized games, and it's gotten good enough that people are complaining that it's good. At the more experimental side, tools like TRELLIS and Hunyuan3D are now able to turn an image (or more reasonable, set of images) into a 3d model, and there's a small industry of specialized auto-rigging tools that theoretically could bring a set of images into a fully-featured video game character.
I don't know Blender enough to judge the outputs (except to say TRELLIS tends to give really holey models). A domain expert like @FCfromSSC might be able to give more light on this topic than I can.
Well, that's not the expert use!
That's a pretty standard git comment, these days, excepting the bit where anyone actually uses and potentially even pays for Antigravity. What's noteworthy is the user tag:
Assuming Torvalds hasn't been paid to advertise, that's a bit of a feather in the cap for AI codegen. The man is notoriously picky about code quality, even for small personal projects, and from a quick read-through (as an admitted python-anti-fan) that seems present here. That's a long way from being useful in a 'real' codebase, nor augmenting his skills in an area he knows well, nor duplicating his skills without his presence, but if you asked me whether I'd prefer to be recognized by a Japanese light novel award, Spotify's Top 50, or Linus Torvalds, I know which one I'd take.
My guesses for how quickly this stuff will progress haven't done great, but anyone got an over:under until a predominately-AI human-review-only commit makes it into the Linux kernel?
Well, that's just trivial stuff!
I don't understand these questions. I don't understand the extent that I don't understand these questions. I'm guessing that some of the publicity is overstated, but I may not be able to evaluate even that. By their own assessment, the advocates of AI-solving Erdős problems people admit:
So it may not even matter. There are a number of red circles, representing failures, and even some green circles of 'success' come with the caveat that the problem was already-solved or even already-solved in a suspiciously similar manner.
Still a lot
smarter aboutbetter at it than I am.Okay, that's the culture. Where's the war?
TEGAKI is a small Japanese art upload site, recently opened to (and then immediately overwhelmed by) widespread applause. Its main offerings are pretty clear:
That's a reasonable and useful service, and if they can manage to pull if off at scale - admittedly a difficult task they don't seem to be solving very well given the current 'maintenance' has a completion estimate of gfl - I could see it taking off. If it doesn't, it describes probably the only plausible (if still imperfect) approach to distinguish AI and human artwork, as AI models are increasingly breaking through limits that gave them their obvious 'tells', and workflows like ControlNet or long inpainting work have made once-unimaginably-complex descriptions now readily available.
That's not the punchline. This is the punchline:
@Porean asked "To which tribe shall the gift of AI fall?" and that was an interesting question a whole (/checks notes/) three years ago. Today, the answer is a bit of a 'mu': the different tribes might rally around flags of "AI" and "anti-AI", but that's not actually going to tell you whether they're using it, nevermind if those uses are beneficial.
In September 2014, XKCD proposed that an algorithm to identify whether a picture contains a bird would take a team of researchers five years. YOLO made that available on a single desktop by 2018, in the sense that I could and did implement training from scratch, personally. A decade after XKCD 1425, you can buy equipment running (heavily stripped-down) equivalents or alternative approaches off the shelf default-on; your cell phone probably does it on someone's server unless you turn cloud functionality it off, and might even then. People who loathe image diffusers love auto-caption assistance that's based around CLIP. Google's default search tool puts an LLM output at the top, and while it was rightfully derided for nearly as year as terrible llama-level output, it's actually gotten good enough in recent months I've started to see anti-AI people use it.
This post used AI translation, because that's default-on for Twitter. I haven't thrown it to ChatGPT or Grok to check whether it's readable or has a coherent theme. Dunno whether it would match my intended them better, or worse, to do so.
AIs can add fairly complex features in fairly large existing codebases. I've tried my hand at 'gamedev but I can't code' and it does work, even for more complex things like wargame AI where it needs to move a bunch of units on a 2D map, consider relative strength and threat, manage pathfinding.
The real issue is making stuff that's actually good. If you left AI to its own devices, it'll produce extremely generic concepts, functional but uninspired. Just try it, tell the AI to one-shot a game of some kind. You'll get the exact median in all areas, boring mechanics, boring opponents, boring kinds of variety.
Human level intelligence has been achieved and achieved some time ago IMO. What's needed is wisdom, extremely long time-horizons and better vision/spatial ability. All of that probably comes with more intelligence but it's subtly different from 'can solve even more bafflingly difficult mathematical tasks' intelligence. In the real world, the mathematics is not the hard part. It's using the mathematics, the physics, the chemistry, as just one part of a long process to create a useful product or technology.
I was speaking with a senior dev at AWS earlier today about AI and coding. Amazon has its own tools for both devs and corp staff and doesn't allow outside tools for anything but simple questions who's output will never be in a work product. He said that one of the bigger surprises for him was how many devs, especially the more junior ones, have adopted using AI for a lot of their coding questions and drastically reduced or stopped using the popular developer forums like StackOverflow for research. He asked a few of them what the main appeal of asking the AI was and they said, even though the AI is often wrong and you have to double check all its answers, it never insults you for knowing less than it does or mocks you for trying to learn something, which was an extrememly common experience on the forums. My own work involves some AI interaction intent-verification where my teams review AI-human interactions for new products to judge how well it captures the person's intentions and the quality of responses. From my POV one of the best things about these AI bot tools it they can't (deliberately) lie, automatically making them better than I'd estimate 75% of the people they will likely replace, who lie constantly.
Yeah it's great for that. You can ask really detailed specific questions, supply lots of context and then ask follow up questions, in real time. Whereas on a forum you're waiting and waiting...
https://stackoverflow.blog/2018/07/10/welcome-wagon-classifying-comments-on-stack-overflow/
To be fair, most humans answering questions on stack overflow are unpaid volunteers. (Sure, a few are Godharding their own score for professional reasons, but the most efficient way of doing this is to plagiarize answers from other people to similar questions.)
Giving advice to people who are advise-resistant can be very frustrating even when you are getting paid for it. Sometimes it emerges that the advice-seeker is planning to do the equivalent of adding helium balloons to a tank to build an air superiority platform, and after a lengthy discussion your only impact is that he is now planning to use hydrogen instead to counter your argument about helium prices.
For me, 99% of the value of stack overflow is that a google search redirects me to a question someone has asked years ago. While it sometimes happen that I try to communicate on IRC, github, SO or the like with random strangers to solve a problem I am having, that is basically an admission of defeat, and I tend not to surrender easily.
The tone on SO should reflect that >90% of the value provided by the site is to passive readers. If you ask a new, interesting, relevant question that is providing a tremendous service to the readers, same as answering such a question. If you are asking a question which was already answered five times because you did not bother to google first, you are wasting everyone's time. If your code or design is shit, then anyone pointing that out is providing a valuable service to the community, given that the question will mainly be read by people with a similar knowledge level.
With IRC (or discord?), this calculation is different, because IRC logs are typically not google-indexed. (Or at least I can not remember finding the answer to a technical question in an IRC log not explicitly generated by a human, ever.) There is not really an audience who is the main beneficiary of the interaction.
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